Plot Nested Marginal Means Results

Plots the cumulative percentage of choices explained by the top attribute levels in order of decisiveness.

Usage

# S3 method for class 'cjdiag_nmm'
plot(
  x,
  top_n = NULL,
  base_size = NULL,
  colors = NULL,
  palette = NULL,
  theme = NULL,
  label_wrap = NULL,
  attribute.names = NULL,
  level.names = NULL,
  ...
)

Arguments

x

A cjdiag_nmm object from cj_fit()

top_n

Number of levels to display (default 25; NULL = all).

base_size

Font size (default from global options or 12)

colors

Named character vector overriding specific palette colors

palette

Palette name: "default", "colorblind", or "grey"

theme

A complete ggplot2::theme() object (overrides all theme defaults)

label_wrap

Character width for label wrapping (default 35)

attribute.names

Named character vector renaming attributes in display

level.names

Named list for renaming levels

...

Additional arguments passed to primary ggplot2 geom

Value

A ggplot object

See also

Other plotting: plot.cjdiag_crt(), plot.cjdiag_forest(), plot.cjdiag_importance(), plot.cjdiag_tree()

Examples

# \donttest{
df <- data.frame(
  y = sample(0:1, 200, TRUE),
  a = factor(sample(c("x","y"), 200, TRUE)),
  b = factor(sample(c("p","q","r"), 200, TRUE)),
  id = rep(1:100, each = 2)
)
nmm <- cj_fit(y ~ a + b, data = df, method = "nmm", resp_id = "id", n_boot = 0)
plot(nmm)

# }